@above : wrote in hurry..so ignore grammatical mistake. :P :P

On Sun, Jan 29, 2012 at 12:27 PM, atul anand <[email protected]>wrote:

> one approach could be following :-
>
> i have check MS-word and found out that for a given incorrect
> words....words suggested are of length = lenght(incorrect_word)+1 or to be
> on a safer side take it as lenght(incorrect_word)+2.
>
> we are assuming that we user is not making mistake greater that
> len(incorret_word)+2;
>
> for for input auw  , suggested words are auk,aiwa,awe,awl,aduwa.
>
> so before running " levenshtein distance " ... check if the given word in
> dictionary passes this test....so here we have narrowed down the sugessted
> items.
>
> you can further refine it by the following ways:-
>
> and all passed strings from above approach , make one more check...
>
> check the similarity between incorrect string and suggested string...
>
> check if incorrectString[i...m]==suggestedString[i...n];
> here we are just checking ascii value of of both strings at position[i];
> this would take O(n)..
> if the difference is not greater that suggested
> strlen(incorrect_string)/2;
>
> obv there could be many string which would pass above test.
> now run this  levenshtein distance B/W incorrect_string and string which
> has passed both of above test... and show only those string whose cost is
> minimum.
>
>
> On Sun, Jan 29, 2012 at 3:07 AM, Ravi Ranjan <[email protected]>wrote:
>
>>  i wanna write the "spell check function"
>>
>> like when we put some word with spelling mistake then it tell the most
>> suitable word matching to it( green error line of spelling in MS-Word)
>>
>> i used  "levenshtein distance " algorithm to find the subset from the
>> dictionary
>>
>> but it is a linear search... and takes much......
>>
>> so is there any other data structure or approach to solve the problem to
>> reduce complexity....... or "levenshtein distance " algorithm can be used
>> in some other way
>>
>>
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>

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